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Identification of the Tumor Boundary of Hilar Cholangiocarcinoma Based on Multiphoton Microscopy.

Authors :
Zhan, Huiling
Sun, Caihong
Luo, Tianyi
Xi, Gangqin
Guo, Yikun
Xu, Mingyu
Chen, Youting
Zhuo, Shuangmu
Source :
IEEE Photonics Journal; Oct2022, Vol. 14 Issue 5, p1-7, 7p
Publication Year :
2022

Abstract

Hilar cholangiocarcinoma (HCC) is a common malignant tumor of the biliary system. The structural characteristics of the bile duct tissue can reflect the changes in its function. The visualization of these specific features is of special significance for understanding the degree of invasion of HCC and tumor borders. Radical R0 resection is the only cure for HCC. Currently, the commonly used medical imaging diagnostic methods can only provide a rough tumor range and require a histopathological analysis. Multiphoton microscopy (MPM) not only has an ultra-high spatial resolution but is also extremely sensitive to collagen fibers with noncentrosymmetric structures. In this study, MPM is applied to image the boundaries of HCC tumors. First, the experimental results show that MPM can clearly reveal the existence of residual cancer cells at the surgical margin. Second, the density of the collagen fibers and the dispersion of the 2D direction angle of the collagen fibers of normal and cancerous tissues are further calculated quantitatively. The collagen fiber signals before and after cancer cell invasion into the different tissues are found to be different. Finally, through a logistic regression prediction curve, combined with the collagen fiber density and 2D direction angle as indicators, it is further judged whether the resection margin is negative, which is closely related to the prognosis of HCC. The experimental results indicate that MPM imaging can serve as a new tool for diagnosing whether the HCC tumor boundary reaches R0 resection. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19430655
Volume :
14
Issue :
5
Database :
Complementary Index
Journal :
IEEE Photonics Journal
Publication Type :
Academic Journal
Accession number :
160730404
Full Text :
https://doi.org/10.1109/JPHOT.2022.3203511